Author

Larry A. Nathanson

Beth Israel Deaconess Medical Center

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Bioinformatics· 3

Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 2 Approach:statistical model· 2 Research Focus:database / resource· 1 Assay:electronic health records· 1 Organism:human· 1 Approach:machine learning (classical)· 1

Frequent Co-Authors

Steven HorngiD· 3 shared David Alexander SontagiD· 2 shared Nathaniel R. GreenbaumiD· 2 shared Foster R. GossiD· 1 shared James C. McClayiD· 1 shared Jeffrey A. NielsoniD· 1 shared Nathan Ivan ShapiroiD· 1 shared Shelley Calder· 1 shared

Activity by Year

2017-2019 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 26 mutual co-author links

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3 shared papersBioinformatics

Steven HorngORCID

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Author profile →

3 papers

Recent·Most cited

Consensus Development Of A Modern Ontology Of Emergency Department Presenting Problems: The HierArchical Presenting Problem OntologY (HaPPy)

Steven Horng, Nathaniel R. Greenbaum, Larry A. Nathanson, James C. McClay, Foster R. Goss, Jeffrey A. Nielson

The paper develops a standardized ontology for emergency department presenting problems using real-world data and expert consensus, achieving high validation accuracy.

Applied Clinical Informatics · May 1, 2019Peer-reviewedBioinformatics

Evaluation of the Angus ICD9-CM Sepsis Abstraction Criteria

Steven Horng, Larry A. Nathanson, David Alexander Sontag, Nathan Ivan Shapiro

The paper evaluates the Angus ICD9-CM sepsis abstraction criteria, finding high specificity but moderate sensitivity in identifying suspected infections in emergency department patients.

bioRxiv · Apr 12, 2017 · PreprintBioinformatics

Contextual Autocomplete: A Novel User Interface Using Machine Learning to Improve Ontology Usage and Structured Data Capture for Presenting Problems in the Emergency Department

Nathaniel R. Greenbaum, Yacine Jernite, Yoni Halpern, Shelley Calder, Larry A. Nathanson, David Alexander Sontag, Steven Horng

This paper demonstrates a contextual autocomplete system that improves structured data capture and quality in emergency department documentation using machine learning.

bioRxiv · Apr 12, 2017 · PreprintBioinformatics